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16 results for “Sequential Patterns”
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Research ArticleOpen accessPhrase in the titleSequential Patterns: A new Corpus-Based Method to Inform the Teaching of Language for Specific PurposesDominique Legallois, Anne PrunetIn this study, we present an original study that aims to show how pedagogically important lexico-grammatical patterns, which are typical of certain genres, can be identified and taught at every educational level, in particular for learners of French for Specific Purposes. These patterns, called Sequential Patterns, constitute a more powerful paradigm than lexical bundles or “P-frames” because they combine different … …Journal of Social Sciences, Vol. 11, Issue 3 · 13 Aug 2015 · 8,174 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEfficient Approach to Discover Interval-Based Sequential PatternsR. Sadasivam, K. DuraiswamyIn most of the sequential pattern mining methodology they have concentrated only on time point base event data. But some research efforts have detailed the mining patterns from time interval based event data. In many application most of the events are occurred at time interval based event not a point based interval for example patient affected by the certain time … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 6,368 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFast Algorithms for Discovering Sequential Patterns in Massive DatasetsS. Dharani, Justus Rabi, Nanda Kumar, DarlyProblem statement: Sequential pattern mining is one of the specific data mining tasks, particularly from retail data. The task is to discover all sequential patterns with a user-specified minimum support, where support of a pattern is the number of data-sequences that contain the pattern. Approach: To find a sequence patterns variety of algorithm like AprioriAll and Generalized Sequential Patterns (GSP) … …Journal of Computer Science, Vol. 7, Issue 9 · 23 Jul 2011 · 7,280 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA New Incremental Updating Algorithm for Mining Sequential PatternsJia-Dong Ren, Xiao-Lei ZhouThis study discusses how to maintain discovered sequential patterns when some information is deleted from a sequence database. A new algorithm, called MA_D (Maintenance Algorithm when Deleting some information), is presented in order to deal with the maintenance of sequential patterns mining resulted from the updating of database and the algorithm makes full use of the information obtained from previous … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 6,613 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Rainfall Forecasting Using Sequential Momentum-Based Artificial Neural Networks for Urban Flood ManagementSherin K K, G. SuganthiUrban floods cause severe disruption in densely populated cities and damage essential public infrastructure. Rapid urbanization and weak drainage systems further increase the risk during heavy rainfall. Accurate short-term rainfall forecasting is required to support early warning and reduce losses. This research focuses on improving rainfall prediction accuracy using an Artificial Neural Network trained with a new optimizer named Sequential … …Journal of Computer Science, Vol. 22, Issue 4 · 9 Apr 2026 · 1,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Systematic Review of Metaheuristic-Metaheuristic (MH-MH) Hybridizations for OptimizationAugustina Dede Agor, Frank Kataka Banaseka, Prince Silas Kwesi Oberko et al.This systematic review following the PRISMA framework analyzes metaheuristic-metaheuristic (MH-MH) hybridizations published between January and October 2024 to uncover patterns of algorithmic dominance, functional roles and integration strategies, metaphor-based partnerships, domain mappings and evaluation orientations. Frequency mapping of 105 canonical algorithms identified Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) as the three most recurrent … …Journal of Computer Science, Vol. 22, Issue 2 · 4 Mar 2026 · 2,183 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,044 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Discovering the Patterns by using PDBD Model in Big DataKamatchi Sundravadivelu, Muthuraman ThangarajBig data is a term that refers to information collected from a wide range of sources, including transaction processing systems, sensors, digital photographs, internet click stream logs, movies, and social media. The goal of text mining is to reveal new patterns and relationships that could lead to the discovery of previously unknown sources. It provides ample scope for interpretation of … …Journal of Computer Science, Vol. 18, Issue 5 · 21 May 2022 · 6,045 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Improvement of SNP Search Using Multithread ProgrammingGeraldo Francisco Donegá Zafalon, Álvaro Magri Nogueira da Cruz, Anderson Rici Amorim et al.Pattern recognition is an important field in Bioinformatics and a well-known task is the search for Single Nucleotide Polymorphism (SNP). It is possible to search for a known SNP position and analyze it using patterns of DNA bases, called masks. Nonetheless, this process becomes computationally expensive as the amount of available genomic data increases. Thus, in this study, we have … …Journal of Computer Science, Vol. 14, Issue 11 · 7 Nov 2018 · 7,734 accessesView PDFCite